Machine Learning Training Performance Engineer

This role bridges the gap between quantitative research and high-performance computing by building and optimizing systems used to train machine learning models at scale. The position focuses on accelerating the end-to-end training lifecycle, including data ingestion, distributed execution, and kernel performance, to enable researchers to iterate more quickly. The engineer will benchmark workloads, optimize distributed training strategies, and collaborate with cross-functional teams to enhance infrastructure efficiency.